- 1. Introduction
- 2. Distributed Approximating Functionals
- 3. One-Dimensional Moment Filter
- 3.1. Time Evolution of Moments
- 3.2. Observation Update and Likelihood Contribution
- 4. Exact One-Dimensional DAF-Filter
- 5. Inference in a Bimodal Potential
- 5.1. The Ginzburg-Landau Model
- 5.2. Accuracy of Time Updates
- 5.3. Maximum-Likelihood Inference
- 6. Higher Dimensional DAF-Filter
- 6.1. Tensorial Eigenvalue Decomposition
- 6.2. Bivariate Diffusion example
- 7. Stochastic Limit Cycle Model
- 8. Conclusions
- References
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